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Data Science Training in OMR

(4.7) 8546 Ratings 9856Learners
100% Job Guarantee | Minimum CTC: ₹ 5.5 LPA
Preview Course Video
  • 40+ Hrs Hands On Training
  • 2 Live Projects For Hands-On Learning
  • 50 Hrs Practical Assignments
  • 24/7 Students

Online Classroom Batches Preferred

20-09-2021
Monday (Monday - Friday)

Weekdays Regular

08:00 AM (IST)

(Class 1Hr - 1:30Hrs) / Per Session

22-09-2021
Thursday (Monday - Friday)

Weekdays Regular

08:00 AM (IST)

(Class 1Hr - 1:30Hrs) / Per Session

25-09-2021
Saturday (Saturday - Sunday)

Weekend Regular

11:00 AM (IST)

(Class 3hr - 3:30Hrs) / Per Session

25-09-2021
Saturday (Saturday - Sunday)

Weekend Fasttrack

11:00 AM (IST)

(Class 4:30Hr - 5:00Hrs) / Per Session

Can't find a batch you were looking for?
₹18000 ₹14500 10% OFF Expires in

No Interest Financing start at ₹ 5000 / month

Data Science Online Training Overview

Data Science training by associate degree business leader on the foremost in-demand Data Science and Machine learning skills. Data Science course within the market, covering the whole Data Science life cycle ideas from Data Extraction, Data Cleansing, knowledge Integration, data processing, building Prediction models, and knowledge image. Skills and tools starting from applied mathematics Analysis, Text mining, Regression models, tongue process (NLP), Hypothesis testing, prognosticative Analytics, Machine Learning, R Studio, Tableau, programming languages like R, Python for the Data Science area unit coated extensively in Data Science training.

Data Science Online Training will:

  • Instructor-Led online training is an associate degree interactive model of training wherever participants and trainer can log in at the constant time and live sessions are going to be done nearly.
  • Hands-on labs and projects add this Data Science certification program bring the ideas to life with our trainers and teaching assistants to guide you on the manner.
  • Our suppliers advanced technical and sensible skills within the assortment, collation, curation, and analysis of Data.
  • These sessions can offer scope for active interaction between you and also the trainer.
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Top Skills You Will Gain
  • R Programmming, Python, SAS
  • Artifical Intelligence
  • Deep Learning
  • Machine Learning
  • Statistics, Naive Bayes
  • Linear Algebra, CART
  • Programming, Neural Networks
  • Data Mining, Visualization

Data Science Course Key Features 100% Money Back Guarantee

  • 5 Weeks Training

    For Become a Expert
  • Certificate of Training

    From Industry Data Science Experts
  • Beginner Friendly

    No Prior Knowledge Required
  • Build 3+ Projects

    For Hands-on Practices
  • Lifetime Access

    To Self-placed Learning
  • Placement Assistance

    To Build Your Career

Top Companies Placement

The data architect is responsible for designing an organization's enterprise data management framework. This framework describes the processes accustomed to set up, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and clean data and is more often rewarded with substantial pay raises as shown below.
  • Designation
  • Annual Salary
    Hiring Companies
  • 4.54L
    Min
  • 7.5L
    Average
  • 18.5L
    Max
  • 5.20L
    Min
  • 9.5L
    Average
  • 18.5L
    Max
  • 6.24L
    Min
  • 8.54L
    Average
  • 17.53L
    Max
  • 5.24L
    Min
  • 8.5L
    Average
  • 19.5L
    Max

Training Options

Class Room Training

Talk to Placement Support

  • Experienced Trainers and Lab Facility Offer By Data Science Course in OMR
  • Best Practice for interview Preparation Techniques
  • Lifetime Access for Student’s Portal, Study Materials, Videos & Top MNC Interview Question

Next Batch Schedule

20-09-2021 (Weekdays Regular)

22-09-2021 (Weekdays Regular)

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Online Training

₹18000₹ 14500

  • preferred
  • Live demonstration of features and practicals Data Science Training in OMR
  • Lifetime access to high-quality self-paced learning and live online class recordings
  • Get complete certification guidance
  • Attend a Free Demo before signing up.

Next Demo Sessions

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Corporate Training

Customized to your team's needs

  • Self-Paced/Live Online/Classroom modes of Data Science Course available
  • Design your own course content based on your project requirements
  • Learn as per full day schedule and/or flexible timings
  • Gain complete guidance on certification
  • 24x7 learner assistance and support

Self Paced Training

  • 50+ Hours High-quality Video
  • 28+ Downloadable Resource
  • Lifetime Access and 24x7 Support
  • Access on Your Computer or Mobile
  • Get Certificate on Course Completion
  • 3+ Projects
12500 ₹4500

Data Science Course Curriculam

Trainers Profile

LearnoVita is filled with the best and top MNC trainers +11 years of highly experienced professionals. As all Trainers are working professionals so they are having many live projects , trainers will use these projects during training sessions . Our trainer will give you technical supports and passionate about data and data-driven decision making.

Pre-requisites

  • Programming : Python , SQL , Scala , Java , R , MATLAB.
  • Machine Learning : Natural Language Processing , Classification , Clustering.
  • Data Visualization : Tableau , SAS , D3.js , Python , Java , R libraries.
  • Big data platforms : MongoDB , Oracle , Microsoft Azure , Cloudera.
  • Syllabus of Data Science Course in OMR Download syllabus

    • What is Data Science, significance of Data Science in today’s digitally-driven world, applications of Data Science, lifecycle of Data Science, components of the Data Science lifecycle, introduction to big data and Hadoop, introduction to Machine Learning and Deep Learning, introduction to R programming and R Studio.
    • Hands-on Exercise - Installation of R Studio, implementing simple mathematical operations and logic using R operators, loops, if statements and switch cases.
    • Introduction to data exploration, importing and exporting data to/from external sources, what is data exploratory analysis, data importing, dataframes, working with dataframes, accessing individual elements, vectors and factors, operators, in-built functions, conditional, looping statements and user-defined functions, matrix, list and array.
    • Hands-on Exercise -Accessing individual elements of customer churn data, modifying and extracting the results from the dataset using user-defined functions in R.
    • Need for Data Manipulation, Introduction to dplyr package, Selecting one or more columns with select() function, Filtering out records on the basis of a condition with filter() function, Adding new columns with the mutate() function, Sampling & Counting with sample_n(), sample_frac() & count() functions, Getting summarized results with the summarise() function, Combining different functions with the pipe operator, Implementing sql like operations with sqldf.
    • Hands-on Exercise -Implementing dplyr to perform various operations for abstracting over how data is manipulated and stored.
    • Introduction to visualization, Different types of graphs, Introduction to grammar of graphics & ggplot2 package, Understanding categorical distribution with geom_bar() function, understanding numerical distribution with geom_hist() function, building frequency polygons with geom_freqpoly(), making a scatter-plot with geom_pont() function, multivariate analysis with geom_boxplot, univariate Analysis with Bar-plot, histogram and Density Plot, multivariate distribution, Bar-plots for categorical variables using geom_bar(), adding themes with the theme() layer, visualization with plotly package & building web applications with shinyR, frequency-plots with geom_freqpoly(), multivariate distribution with scatter-plots and smooth lines, continuous vs categorical with box-plots, subgrouping the plots, working with co-ordinates and themes to make the graphs more presentable, Intro to plotly & various plots, visualization with ggvis package, geographic visualization with ggmap(), building web applications with shinyR.
    • Hands-on Exercise -Creating data visualization to understand the customer churn ratio using charts using ggplot2, Plotly for importing and analyzing data into grids. You will visualize tenure, monthly charges, total charges and other individual columns by using the scatter plot.
    • Why do we need Statistics?, Categories of Statistics, Statistical Terminologies,Types of Data, Measures of Central Tendency, Measures of Spread, Correlation & Covariance,Standardization & Normalization,Probability & Types of Probability, Hypothesis Testing, Chi-Square testing, ANOVA, normal distribution, binary distribution.
    • Hands-on Exercise -– Building a statistical analysis model that uses quantifications, representations, experimental data for gathering, reviewing, analyzing and drawing conclusions from data.
    • Introduction to Machine Learning, introduction to Linear Regression, predictive modeling with Linear Regression, simple Linear and multiple Linear Regression, concepts and formulas, assumptions and residual diagnostics in Linear Regression, building simple linear model, predicting results and finding p-value, introduction to logistic regression, comparing linear regression and logistics regression, bivariate & multi-variate logistic regression, confusion matrix & accuracy of model, threshold evaluation with ROCR, Linear Regression concepts and detailed formulas, various assumptions of Linear Regression,residuals, qqnorm(), qqline(), understanding the fit of the model, building simple linear model, predicting results and finding p-value, understanding the summary results with Null Hypothesis, p-value & F-statistic, building linear models with multiple independent variables.
    • Hands-on Exercise -Modeling the relationship within the data using linear predictor functions. Implementing Linear & Logistics Regression in R by building model with ‘tenure’ as dependent variable and multiple independent variables.
    • Introduction to Logistic Regression, Logistic Regression Concepts, Linear vs Logistic regression, math behind Logistic Regression, detailed formulas, logit function and odds, Bi-variate logistic Regression, Poisson Regression, building simple “binomial” model and predicting result, confusion matrix and Accuracy, true positive rate, false positive rate, and confusion matrix for evaluating built model, threshold evaluation with ROCR, finding the right threshold by building the ROC plot, cross validation & multivariate logistic regression, building logistic models with multiple independent variables, real-life applications of Logistic Regression
    • Hands-on Exercise -Implementing predictive analytics by describing the data and explaining the relationship between one dependent binary variable and one or more binary variables. You will use glm() to build a model and use ‘Churn’ as the dependent variable.
    • What is classification and different classification techniques, introduction to Decision Tree, algorithm for decision tree induction, building a decision tree in R, creating a perfect Decision Tree, Confusion Matrix, Regression trees vs Classification trees, introduction to ensemble of trees and bagging, Random Forest concept, implementing Random Forest in R, what is Naive Bayes, Computing Probabilities, Impurity Function – Entropy, understand the concept of information gain for right split of node, Impurity Function – Information gain, understand the concept of Gini index for right split of node, Impurity Function – Gini index, understand the concept of Entropy for right split of node, overfitting & pruning, pre-pruning, post-pruning, cost-complexity pruning, pruning decision tree and predicting values, find the right no of trees and evaluate performance metrics.
    • Hands-on Exercise -Implementing Random Forest for both regression and classification problems. You will build a tree, prune it by using ‘churn’ as the dependent variable and build a Random Forest with the right number of trees, using ROCR for performance metrics.
    • What is Clustering & it’s Use Cases, what is K-means Clustering, what is Canopy Clustering, what is Hierarchical Clustering, introduction to Unsupervised Learning, feature extraction & clustering algorithms, k-means clustering algorithm, Theoretical aspects of k-means, and k-means process flow, K-means in R, implementing K-means on the data-set and finding the right no. of clusters using Scree-plot, hierarchical clustering & Dendogram, understand Hierarchical clustering, implement it in R and have a look at Dendograms, Principal Component Analysis, explanation of Principal Component Analysis in detail, PCA in R, implementing PCA in R.
    • Hands-on Exercise -Deploying unsupervised learning with R to achieve clustering and dimensionality reduction, K-means clustering for visualizing and interpreting results for the customer churn data
    • Introduction to association rule Mining & Market Basket Analysis, measures of Association Rule Mining: Support, Confidence, Lift, Apriori algorithm & implementing it in R, Introduction to Recommendation Engine, user-based collaborative filtering & Item-Based Collaborative Filtering, implementing Recommendation Engine in R, user-Based and item-Based, Recommendation Use-cases.
    • Hands-on Exercise -Deploying association analysis as a rule-based machine learning method, identifying strong rules discovered in databases with measures based on interesting discoveries.
    • Introducing Artificial Intelligence and Deep Learning, what is an Artificial Neural Network, TensorFlow – computational framework for building AI models, fundamentals of building ANN using TensorFlow, working with TensorFlow in R.
    • What is Time Series, techniques and applications, components of Time Series, moving average, smoothing techniques, exponential smoothing, univariate time series models, multivariate time series analysis, Arima model, Time Series in R, sentiment analysis in R (Twitter sentiment analysis), text analysis.
    • Hands-on Exercise -Analyzing time series data, sequence of measurements that follow a non-random order to identify the nature of phenomenon and to forecast the future values in the series.
    • Introduction to Support Vector Machine (SVM), Data classification using SVM, SVM Algorithms using Separable and Inseparable cases, Linear SVM for identifying margin hyperplane.
    • What is Bayes theorem, What is Naïve Bayes Classifier, Classification Workflow, How Naive Bayes classifier works, Classifier building in Scikit-learn, building a probabilistic classification model using Naïve Bayes, Zero Probability Problem.
    • Introduction to concepts of Text Mining, Text Mining use cases, understanding and manipulating text with ‘tm’ & ‘stringR’, Text Mining Algorithms, Quantification of Text, Term Frequency-Inverse Document Frequency (TF-IDF), After TF-IDF.
    • This case study is associated with the modeling technique of Market Basket Analysis where you will learn about loading of data, various techniques for plotting the items and running the algorithms. It includes finding out what are the items that go hand in hand and hence can be clubbed together. This is used for various real world scenarios like a supermarket shopping cart and so on.
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    Industry Projects

    Project 1
    Wallmart Sales Data Set

    Retail is another industry that extensively uses analytics to optimize business processes.

    Project 2
    Flipkart Classification Dataset

    This project is to forecast sales for each department and increasing labelled dataset using semi-supervised classification.

    Project 3
    Credit Card Fraud Detection

    The project consist of data analysis for various parameters of banking dataset and data visualization for finding the probability of occurrence of fraudulent activities.

    Mock Interviews

    • Mock interviews by Learnovita give you the platform to prepare, practice and experience the real-life job interview. Familiarizing yourself with the interview environment beforehand in a relaxed and stress-free environment gives you an edge over your peers.
    • In our mock interviews will be conducted by industry best Data Science Course in OMR experts with an average experience of 7+ years. So you’re sure to improve your chances of getting hired!

    How Learnovita Mock Interview Works?

    Data Science Course Objectives

    • The time it takes to become a data scientist is determined by your career goals as well as the amount of money and time you are willing to invest in your education. There are four-year bachelor's degrees in data science as well as three-month boot camps available. If you already have a bachelor's degree or have completed a Bootcamp, you may want to consider pursuing a master's degree, which can be completed in as little as one year. According to the Burtch Works study, the majority of data scientists have a graduate degree.
    • All you need to become a Data Scientist is the desire and passion to pursue a career as a data scientist. The first step in beginning your learning journey is to learn about Data Science and its prerequisites. Enrolling in the Best Data Science program offered by a reputable institute would be the best way to make your dream a reality. Constant learning and practice would land you the dream job.
    • There are numerous reasons why data science is one of the best career options in the twenty-first century. The demand and scope of this technology are the primary motivators for many people to pursue a career in this platform. Furthermore, the pay scale offered in this sector is piquing the interest of young people in becoming Data Scientists. The job roles available in this domain are recognized as among the highest paid in the country. As data science continues to expand its impact across multiple fields, it is expected to replace many existing job roles. As a result, data science is the best option for anyone looking for a stable career.
    • Yes, statistics are an important aspect of data science, and having a solid understanding of the various statistical concepts is one of the major prerequisites for mastering the Data Science Course. Statistics are essential for grasping the concepts of Machine Learning. Statistics make it simple to understand how Data Science concepts can be applied to problem-solving.
    • Data scientists employ a wide range of skills, depending on the industry and job responsibilities. The majority of data scientists are familiar with programming languages like R and Python, as well as statistical analysis, data visualization, machine learning techniques, data cleaning, research, and data warehouses and structures.
    • Data Science is one of the highest-paying jobs. Data Scientists earn an average of $116,100 per year, according to Glassdoor. As a result, Data Science is a highly lucrative career option.
    • A data science internship is a sure-fire way to understand the domain while also gaining hands-on experience in this field. Many final-year graduate students are excited about a career in this cutting-edge field. Learn about some of the fundamental skills needed to land a data science internship.
    • Computer Science is a technical skill.
    • Python is a programming language. Python, along with Java, Perl, and C/C++, is the most common coding language I see required in data science roles.
    • Platform for Hadoop.
    • SQL Database and Coding.
    • Spark is an acronym for Apache Spark.
    • AI and machine learning.
    • Visualization of data.
    • Data that is unstructured.
    • The future is data. Data science is expected to have a bright future in the coming years, and data scientists are expected to have a rewarding career path as well. Data Science has had a significant impact on the various fields in which it has been applied. Data science is expected to expand its enclave into many other fields and create new dynamics, in addition to replacing many existing jobs. In this world, there are approximately 1 lakh job opportunities for various job roles in the field of Data Science.
    • yes,To summarise, data science certificates are unlikely to help you much in your job applications, especially at the early pass/fail stage of resume assessment, so you shouldn't focus on questions like "which data science certificate is best?" when deciding where to pursue data science education.
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    Exam & Certification

    At LearnoVita, You Can Enroll in Either the instructor-led Data Science Online Course, Classroom Training or Online Self-Paced Training.



    Data Science Online Training / Class Room:

    • Participate and Complete One batch of Data Science Course Course
    • Successful completion and evaluation of any one of the given projects

    Data Science Online Self-learning:

    • Complete 85% of the Data Science Certification Training
    • Successful completion and evaluation of any one of the given projects
    Honestly Yes, LearnoVita Provide 1 Set of Practice test as part of Your Data Science Certification Course in OMR. It helps you to prepare for the actual Data Science Certification Training exam. You can try this free Data Science Fundamentals Practice Test to Understand the Various type of tests that are Comes Under the Parts of Course Curriculum at LearnoVita.

    These are the Different Kinds of Certification levels that was Structured under the Data Science Certification Path.

    • Certified Analytics Professional (CAP)
    • Cloudera Certified Associate: Data Analyst
    • Cloudera Certified Professional: CCP Data Engineer
    • Data Science Council of America (DASCA) Senior Data Scientist (SDS)
    • Data Science Council of America (DASCA) Principle Data Scientist (PDS)
    • Dell EMC Data Science Track
    • Google Certified Professional Data Engineer
    • Google Data and Machine Learning
    • IBM Data Science Professional Certificate
    • Microsoft MCSE: Data Management and Analytics
    • Microsoft Certified Azure Data Scientist Associate
    • Open Certified Data Scientist (Open CDS)
    • SAS Certified Advanced Analytics Professional
    • SAS Certified Big Data Professional
    • SAS Certified Data Scientist
    • Learn About the Certification Paths.
    • Write Code Daily This will help you develop Coding Reading and Writing ability.
    • Refer and Read Recommended Books Depending on Which Exam you are Going to Take up.
    • Join LernoVita Data Science Certification Training in OMR That Gives you a High Chance to interact with your Subject Expert Instructors and fellow Aspirants Preparing for Certifications.
    • Solve Sample Tests that would help you to Increase the Speed needed for attempting the exam and also helps for Agile Thinking.
    Honestly Yes, Please refer to the link This Would Guide you with the Top 20 Interview Questions & Answers for Data Science Developers.

    Data Science Course FAQ's

    LearnoVita Offers a good discount percentage for you CALL at +91 93833 99991 and know the Exciting offers Available for you!!!
    Yes, you can attend the demo session. Even though We have a limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrolment is not possible.If you are unable to attend you can go through our Pre recorded session of the same trainer, it would give you a clear insight about how the classes are conducted, the quality of instructors, and the level of interaction in the class.
    All Our instructors from Data Science Classes in OMR are working professionals from the Industries, Working in leading Organizations and have Real-World Experience with Minimum 9-12 yrs of Relevant IT field Experience. All these experienced folks at LearnoVita Provide a Great learning experience.
    The trainer will give Server Access to the course seekers, and we make sure you acquire practical hands-on training by providing you with every utility that is needed for your understanding of the course
    • LearnoVita Best Data Science Course in OMR will assist the job seekers to Seek, Connect & Succeed and delight the employers with the perfect candidates.
    • On Successfully Completing a Career Course from LearnoVita Best Data Science Course in OMR, you Could be Eligible for Job Placement Assistance.
    • 100% Placement Assistance* - We have strong relationship with over 650+ Top MNCs, When a student completes his/ her course successfully, LearnoVita Placement Cell helps him/ her interview with Major Companies like Oracle, HP, Wipro, Accenture, Google, IBM, Tech Mahindra, Amazon, CTS, TCS, HCL, Infosys, MindTree and MPhasis etc...
    • LearnoVita is the Legend in offering placement to the students. Please visit our Placed Students's List on our website.
    • More than 5400+ students placed in last year in India & Globally.
    • LearnoVita is the Best Data Science Course Institute in OMR Offers mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
    • 85% percent placement record
    • Our Placement Cell support you till you get placed in better MNC
    • Please Visit Your Student's Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
    After Your Course Completion You will Receive
    • LearnoVita Certification is Accredited by all major Global Companies around the World.
    • LearnoVita is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of Data Science and National Institute of Education (nie) Singapore
    • Also, LearnoVita Technical Experts Help's People Who Want to Clear the National Authorized Certificate in Specialized IT Domain.
    • LearnoVita is offering you the most updated Data Science certification training in OMR, relevant, and high-value real-world projects as part of the training program.
    • All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
    • You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc.
    • After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.
    At LearnoVita you can enroll in either the instructor-led Data Science Online Course, Self-Paced Training, Class Room, One to One Training, Fast Track, Customized Training & Online Training Mode. Apart from this, LearnoVita also offers Corporate Training for organizations to UPSKILL their workforce.
    LearnoVita Assures You will Never lose any Topics and Modules. You can choose either of the Three options:
    • We will reschedule the Data Science classes in OMR as per your convenience within the stipulated course duration with all such possibilities.
    • View the class presentation and recordings that are available for online viewing.
    • You can attend the missed session, in any other live batch.
    Just give us a CALL at +91 9383399991 OR email at contact@learnovita.com
    Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question After Once You Have Enrolled.
    We at LearnoVita believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics and Can Access more information and Richer Understanding through teacher and other students' body language and voice. Therefore, we restrict the size of each Data Science batch to 5 or 6 members
    Learning Data Science can help open up many opportunities for your career. It is a GREAT SKILL-SET to have as many developer roles in the job market requires proficiency in Data Science. Mastering Data Science can help you get started with your career in IT. Companies like Oracle, IBM, Wipro, HP, HCL, DELL, Bosch, Capgemini, Accenture, Mphasis, Paypal, and MindLabs.
    The Average salary of Data Science Developer in India is ₹4,43,568 per annum.
    You can contact our support number at +91 93800 99996 / Directly can do by LearnoVita E-commerce payment system Login or directly walk-in to one of the LearnoVita branches in India.
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